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Human Capital in Growth Regressions: How Much Difference Does Data Quality Make?

Author

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  • Angel de la Fuente

    (Instituto de Análisis Económico (CSIC) and CREA.)

  • Rafael Doménech

    (Universidad de Valencia.)

Abstract

We construct estimates of educational attainment for a sample of 21 OECD countries. Our series incorporate previously unexploited information and remove sharp breaks in the data that can only reflect changes in classification criteria. We then construct indicators of the information content of our estimates and a number of previously available data sets and examine their performance in several growth specifications. We find a clear positive correlation between data quality and the size and significance of human capital coefficients in growth regressions. Using an extension of the classical errors in variables model to correct for measurement error bias, we construct a set of meta-estimates of the coefficient of years of schooling in an aggregate Cobb-Douglas production function. Our results suggest that the value of this parameter is likely to be above 0.60. (JEL: O40, I20, O30, C19) Copyright (c) 2006 by the European Economic Association.

Suggested Citation

  • Angel de la Fuente & Rafael Doménech, 2006. "Human Capital in Growth Regressions: How Much Difference Does Data Quality Make?," Journal of the European Economic Association, MIT Press, vol. 4(1), pages 1-36, March.
    • Handle: RePEc:tpr:jeurec:v:4:y:2006:i:1:p:1-36
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    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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